Inversion of light scattering data by singular system analysis

We consider the problem of inverting experimental data obtained in light scattering experiments described by linear theories. We discuss applications to particle sizing and we describe fast and easy-to-implement algorithms which permit the extraction, from noisy measurements, of reliable information about the particle size distribution. © 1987, SPIE.

Extraction of polydispersity information from photon correlation data

Photon correlation spectroscopy (PCS) is a light-scattering technique for particle size diagnosis. It has been used mainly in the investigation of hydrosol particles since it is based on the measurement of the correlation function of the light scattered from the Brownian motion of suspended particles. Recently this technique also proved useful for studying soot particles in flames and similar aerosol systems. In the case of a polydispersed system the problem of recovering the particle size distribution can be reduced to the problem of inverting the Laplace transform. In this paper we review several methods introduced by the authors for the solution of this problem. We present some numerical results and we discuss the resolution limits characterizing the reconstruction of the size distributions. © 1989.